WARNING:tensorflow:From D:\DocumentsDDrive\Installed_Files\Anaconda3\envs\tf-gpu\lib\site-packages\tensorflow\python\keras\initializers.py:104: calling VarianceScaling.__init__ (from tensorflow.python.ops.init_ops) with distribution=normal is deprecated and will be removed in a future version.
Instructions for updating:
`normal` is a deprecated alias for `truncated_normal`
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_1 (InputLayer) (None, 96, 96, 3) 0
__________________________________________________________________________________________________
conv2d (Conv2D) (None, 47, 47, 32) 896 input_1[0][0]
__________________________________________________________________________________________________
conv2d_1 (Conv2D) (None, 45, 45, 32) 9248 conv2d[0][0]
__________________________________________________________________________________________________
conv2d_2 (Conv2D) (None, 45, 45, 64) 18496 conv2d_1[0][0]
__________________________________________________________________________________________________
max_pooling2d (MaxPooling2D) (None, 22, 22, 64) 0 conv2d_2[0][0]
__________________________________________________________________________________________________
conv2d_3 (Conv2D) (None, 22, 22, 96) 55392 conv2d_2[0][0]
__________________________________________________________________________________________________
concatenate (Concatenate) (None, 22, 22, 160) 0 max_pooling2d[0][0]
conv2d_3[0][0]
__________________________________________________________________________________________________
conv2d_6 (Conv2D) (None, 22, 22, 64) 10304 concatenate[0][0]
__________________________________________________________________________________________________
conv2d_7 (Conv2D) (None, 22, 22, 64) 28736 conv2d_6[0][0]
__________________________________________________________________________________________________
conv2d_4 (Conv2D) (None, 22, 22, 64) 10304 concatenate[0][0]
__________________________________________________________________________________________________
conv2d_8 (Conv2D) (None, 22, 22, 64) 28736 conv2d_7[0][0]
__________________________________________________________________________________________________
conv2d_5 (Conv2D) (None, 20, 20, 96) 55392 conv2d_4[0][0]
__________________________________________________________________________________________________
conv2d_9 (Conv2D) (None, 20, 20, 96) 55392 conv2d_8[0][0]
__________________________________________________________________________________________________
concatenate_1 (Concatenate) (None, 20, 20, 192) 0 conv2d_5[0][0]
conv2d_9[0][0]
__________________________________________________________________________________________________
conv2d_10 (Conv2D) (None, 9, 9, 192) 331968 concatenate_1[0][0]
__________________________________________________________________________________________________
zero_padding2d (ZeroPadding2D) (None, 10, 10, 192) 0 conv2d_10[0][0]
__________________________________________________________________________________________________
max_pooling2d_1 (MaxPooling2D) (None, 10, 10, 192) 0 concatenate_1[0][0]
__________________________________________________________________________________________________
concatenate_2 (Concatenate) (None, 10, 10, 384) 0 zero_padding2d[0][0]
max_pooling2d_1[0][0]
__________________________________________________________________________________________________
batch_normalization (BatchNorma (None, 10, 10, 384) 1536 concatenate_2[0][0]
__________________________________________________________________________________________________
conv2d_15 (Conv2D) (None, 10, 10, 32) 12320 batch_normalization[0][0]
__________________________________________________________________________________________________
average_pooling2d (AveragePooli (None, 10, 10, 384) 0 batch_normalization[0][0]
__________________________________________________________________________________________________
conv2d_13 (Conv2D) (None, 10, 10, 32) 12320 batch_normalization[0][0]
__________________________________________________________________________________________________
conv2d_16 (Conv2D) (None, 10, 10, 48) 13872 conv2d_15[0][0]
__________________________________________________________________________________________________
conv2d_11 (Conv2D) (None, 10, 10, 48) 18480 average_pooling2d[0][0]
__________________________________________________________________________________________________
conv2d_12 (Conv2D) (None, 10, 10, 48) 18480 batch_normalization[0][0]
__________________________________________________________________________________________________
conv2d_14 (Conv2D) (None, 10, 10, 48) 13872 conv2d_13[0][0]
__________________________________________________________________________________________________
conv2d_17 (Conv2D) (None, 10, 10, 48) 20784 conv2d_16[0][0]
__________________________________________________________________________________________________
concatenate_3 (Concatenate) (None, 10, 10, 192) 0 conv2d_11[0][0]
conv2d_12[0][0]
conv2d_14[0][0]
conv2d_17[0][0]
__________________________________________________________________________________________________
batch_normalization_1 (BatchNor (None, 10, 10, 192) 768 concatenate_3[0][0]
__________________________________________________________________________________________________
conv2d_22 (Conv2D) (None, 10, 10, 32) 6176 batch_normalization_1[0][0]
__________________________________________________________________________________________________
average_pooling2d_1 (AveragePoo (None, 10, 10, 192) 0 batch_normalization_1[0][0]
__________________________________________________________________________________________________
conv2d_20 (Conv2D) (None, 10, 10, 32) 6176 batch_normalization_1[0][0]
__________________________________________________________________________________________________
conv2d_23 (Conv2D) (None, 10, 10, 48) 13872 conv2d_22[0][0]
__________________________________________________________________________________________________
conv2d_18 (Conv2D) (None, 10, 10, 48) 9264 average_pooling2d_1[0][0]
__________________________________________________________________________________________________
conv2d_19 (Conv2D) (None, 10, 10, 48) 9264 batch_normalization_1[0][0]
__________________________________________________________________________________________________
conv2d_21 (Conv2D) (None, 10, 10, 48) 13872 conv2d_20[0][0]
__________________________________________________________________________________________________
conv2d_24 (Conv2D) (None, 10, 10, 48) 20784 conv2d_23[0][0]
__________________________________________________________________________________________________
concatenate_4 (Concatenate) (None, 10, 10, 192) 0 conv2d_18[0][0]
conv2d_19[0][0]
conv2d_21[0][0]
conv2d_24[0][0]
__________________________________________________________________________________________________
batch_normalization_2 (BatchNor (None, 10, 10, 192) 768 concatenate_4[0][0]
__________________________________________________________________________________________________
conv2d_29 (Conv2D) (None, 10, 10, 32) 6176 batch_normalization_2[0][0]
__________________________________________________________________________________________________
average_pooling2d_2 (AveragePoo (None, 10, 10, 192) 0 batch_normalization_2[0][0]
__________________________________________________________________________________________________
conv2d_27 (Conv2D) (None, 10, 10, 32) 6176 batch_normalization_2[0][0]
__________________________________________________________________________________________________
conv2d_30 (Conv2D) (None, 10, 10, 48) 13872 conv2d_29[0][0]
__________________________________________________________________________________________________
conv2d_25 (Conv2D) (None, 10, 10, 48) 9264 average_pooling2d_2[0][0]
__________________________________________________________________________________________________
conv2d_26 (Conv2D) (None, 10, 10, 48) 9264 batch_normalization_2[0][0]
__________________________________________________________________________________________________
conv2d_28 (Conv2D) (None, 10, 10, 48) 13872 conv2d_27[0][0]
__________________________________________________________________________________________________
conv2d_31 (Conv2D) (None, 10, 10, 48) 20784 conv2d_30[0][0]
__________________________________________________________________________________________________
concatenate_5 (Concatenate) (None, 10, 10, 192) 0 conv2d_25[0][0]
conv2d_26[0][0]
conv2d_28[0][0]
conv2d_31[0][0]
__________________________________________________________________________________________________
batch_normalization_3 (BatchNor (None, 10, 10, 192) 768 concatenate_5[0][0]
__________________________________________________________________________________________________
conv2d_36 (Conv2D) (None, 10, 10, 32) 6176 batch_normalization_3[0][0]
__________________________________________________________________________________________________
average_pooling2d_3 (AveragePoo (None, 10, 10, 192) 0 batch_normalization_3[0][0]
__________________________________________________________________________________________________
conv2d_34 (Conv2D) (None, 10, 10, 32) 6176 batch_normalization_3[0][0]
__________________________________________________________________________________________________
conv2d_37 (Conv2D) (None, 10, 10, 48) 13872 conv2d_36[0][0]
__________________________________________________________________________________________________
conv2d_32 (Conv2D) (None, 10, 10, 48) 9264 average_pooling2d_3[0][0]
__________________________________________________________________________________________________
conv2d_33 (Conv2D) (None, 10, 10, 48) 9264 batch_normalization_3[0][0]
__________________________________________________________________________________________________
conv2d_35 (Conv2D) (None, 10, 10, 48) 13872 conv2d_34[0][0]
__________________________________________________________________________________________________
conv2d_38 (Conv2D) (None, 10, 10, 48) 20784 conv2d_37[0][0]
__________________________________________________________________________________________________
concatenate_6 (Concatenate) (None, 10, 10, 192) 0 conv2d_32[0][0]
conv2d_33[0][0]
conv2d_35[0][0]
conv2d_38[0][0]
__________________________________________________________________________________________________
batch_normalization_4 (BatchNor (None, 10, 10, 192) 768 concatenate_6[0][0]
__________________________________________________________________________________________________
conv2d_40 (Conv2D) (None, 10, 10, 192) 37056 batch_normalization_4[0][0]
__________________________________________________________________________________________________
conv2d_41 (Conv2D) (None, 10, 10, 224) 387296 conv2d_40[0][0]
__________________________________________________________________________________________________
max_pooling2d_2 (MaxPooling2D) (None, 4, 4, 192) 0 batch_normalization_4[0][0]
__________________________________________________________________________________________________
conv2d_39 (Conv2D) (None, 4, 4, 384) 663936 batch_normalization_4[0][0]
__________________________________________________________________________________________________
conv2d_42 (Conv2D) (None, 4, 4, 256) 516352 conv2d_41[0][0]
__________________________________________________________________________________________________
concatenate_7 (Concatenate) (None, 4, 4, 832) 0 max_pooling2d_2[0][0]
conv2d_39[0][0]
conv2d_42[0][0]
__________________________________________________________________________________________________
batch_normalization_5 (BatchNor (None, 4, 4, 832) 3328 concatenate_7[0][0]
__________________________________________________________________________________________________
conv2d_48 (Conv2D) (None, 4, 4, 96) 79968 batch_normalization_5[0][0]
__________________________________________________________________________________________________
conv2d_49 (Conv2D) (None, 4, 4, 96) 64608 conv2d_48[0][0]
__________________________________________________________________________________________________
conv2d_45 (Conv2D) (None, 4, 4, 96) 79968 batch_normalization_5[0][0]
__________________________________________________________________________________________________
conv2d_50 (Conv2D) (None, 4, 4, 112) 75376 conv2d_49[0][0]
__________________________________________________________________________________________________
average_pooling2d_4 (AveragePoo (None, 4, 4, 832) 0 batch_normalization_5[0][0]
__________________________________________________________________________________________________
conv2d_46 (Conv2D) (None, 4, 4, 112) 75376 conv2d_45[0][0]
__________________________________________________________________________________________________
conv2d_51 (Conv2D) (None, 4, 4, 112) 87920 conv2d_50[0][0]
__________________________________________________________________________________________________
conv2d_43 (Conv2D) (None, 4, 4, 64) 53312 average_pooling2d_4[0][0]
__________________________________________________________________________________________________
conv2d_44 (Conv2D) (None, 4, 4, 192) 159936 batch_normalization_5[0][0]
__________________________________________________________________________________________________
conv2d_47 (Conv2D) (None, 4, 4, 128) 100480 conv2d_46[0][0]
__________________________________________________________________________________________________
conv2d_52 (Conv2D) (None, 4, 4, 128) 100480 conv2d_51[0][0]
__________________________________________________________________________________________________
concatenate_8 (Concatenate) (None, 4, 4, 512) 0 conv2d_43[0][0]
conv2d_44[0][0]
conv2d_47[0][0]
conv2d_52[0][0]
__________________________________________________________________________________________________
batch_normalization_6 (BatchNor (None, 4, 4, 512) 2048 concatenate_8[0][0]
__________________________________________________________________________________________________
conv2d_58 (Conv2D) (None, 4, 4, 96) 49248 batch_normalization_6[0][0]
__________________________________________________________________________________________________
conv2d_59 (Conv2D) (None, 4, 4, 96) 64608 conv2d_58[0][0]
__________________________________________________________________________________________________
conv2d_55 (Conv2D) (None, 4, 4, 96) 49248 batch_normalization_6[0][0]
__________________________________________________________________________________________________
conv2d_60 (Conv2D) (None, 4, 4, 112) 75376 conv2d_59[0][0]
__________________________________________________________________________________________________
average_pooling2d_5 (AveragePoo (None, 4, 4, 512) 0 batch_normalization_6[0][0]
__________________________________________________________________________________________________
conv2d_56 (Conv2D) (None, 4, 4, 112) 75376 conv2d_55[0][0]
__________________________________________________________________________________________________
conv2d_61 (Conv2D) (None, 4, 4, 112) 87920 conv2d_60[0][0]
__________________________________________________________________________________________________
conv2d_53 (Conv2D) (None, 4, 4, 64) 32832 average_pooling2d_5[0][0]
__________________________________________________________________________________________________
conv2d_54 (Conv2D) (None, 4, 4, 192) 98496 batch_normalization_6[0][0]
__________________________________________________________________________________________________
conv2d_57 (Conv2D) (None, 4, 4, 128) 100480 conv2d_56[0][0]
__________________________________________________________________________________________________
conv2d_62 (Conv2D) (None, 4, 4, 128) 100480 conv2d_61[0][0]
__________________________________________________________________________________________________
concatenate_9 (Concatenate) (None, 4, 4, 512) 0 conv2d_53[0][0]
conv2d_54[0][0]
conv2d_57[0][0]
conv2d_62[0][0]
__________________________________________________________________________________________________
batch_normalization_7 (BatchNor (None, 4, 4, 512) 2048 concatenate_9[0][0]
__________________________________________________________________________________________________
conv2d_68 (Conv2D) (None, 4, 4, 96) 49248 batch_normalization_7[0][0]
__________________________________________________________________________________________________
conv2d_69 (Conv2D) (None, 4, 4, 96) 64608 conv2d_68[0][0]
__________________________________________________________________________________________________
conv2d_65 (Conv2D) (None, 4, 4, 96) 49248 batch_normalization_7[0][0]
__________________________________________________________________________________________________
conv2d_70 (Conv2D) (None, 4, 4, 112) 75376 conv2d_69[0][0]
__________________________________________________________________________________________________
average_pooling2d_6 (AveragePoo (None, 4, 4, 512) 0 batch_normalization_7[0][0]
__________________________________________________________________________________________________
conv2d_66 (Conv2D) (None, 4, 4, 112) 75376 conv2d_65[0][0]
__________________________________________________________________________________________________
conv2d_71 (Conv2D) (None, 4, 4, 112) 87920 conv2d_70[0][0]
__________________________________________________________________________________________________
conv2d_63 (Conv2D) (None, 4, 4, 64) 32832 average_pooling2d_6[0][0]
__________________________________________________________________________________________________
conv2d_64 (Conv2D) (None, 4, 4, 192) 98496 batch_normalization_7[0][0]
__________________________________________________________________________________________________
conv2d_67 (Conv2D) (None, 4, 4, 128) 100480 conv2d_66[0][0]
__________________________________________________________________________________________________
conv2d_72 (Conv2D) (None, 4, 4, 128) 100480 conv2d_71[0][0]
__________________________________________________________________________________________________
concatenate_10 (Concatenate) (None, 4, 4, 512) 0 conv2d_63[0][0]
conv2d_64[0][0]
conv2d_67[0][0]
conv2d_72[0][0]
__________________________________________________________________________________________________
batch_normalization_8 (BatchNor (None, 4, 4, 512) 2048 concatenate_10[0][0]
__________________________________________________________________________________________________
conv2d_78 (Conv2D) (None, 4, 4, 96) 49248 batch_normalization_8[0][0]
__________________________________________________________________________________________________
conv2d_79 (Conv2D) (None, 4, 4, 96) 64608 conv2d_78[0][0]
__________________________________________________________________________________________________
conv2d_75 (Conv2D) (None, 4, 4, 96) 49248 batch_normalization_8[0][0]
__________________________________________________________________________________________________
conv2d_80 (Conv2D) (None, 4, 4, 112) 75376 conv2d_79[0][0]
__________________________________________________________________________________________________
average_pooling2d_7 (AveragePoo (None, 4, 4, 512) 0 batch_normalization_8[0][0]
__________________________________________________________________________________________________
conv2d_76 (Conv2D) (None, 4, 4, 112) 75376 conv2d_75[0][0]
__________________________________________________________________________________________________
conv2d_81 (Conv2D) (None, 4, 4, 112) 87920 conv2d_80[0][0]
__________________________________________________________________________________________________
conv2d_73 (Conv2D) (None, 4, 4, 64) 32832 average_pooling2d_7[0][0]
__________________________________________________________________________________________________
conv2d_74 (Conv2D) (None, 4, 4, 192) 98496 batch_normalization_8[0][0]
__________________________________________________________________________________________________
conv2d_77 (Conv2D) (None, 4, 4, 128) 100480 conv2d_76[0][0]
__________________________________________________________________________________________________
conv2d_82 (Conv2D) (None, 4, 4, 128) 100480 conv2d_81[0][0]
__________________________________________________________________________________________________
concatenate_11 (Concatenate) (None, 4, 4, 512) 0 conv2d_73[0][0]
conv2d_74[0][0]
conv2d_77[0][0]
conv2d_82[0][0]
__________________________________________________________________________________________________
batch_normalization_9 (BatchNor (None, 4, 4, 512) 2048 concatenate_11[0][0]
__________________________________________________________________________________________________
conv2d_88 (Conv2D) (None, 4, 4, 96) 49248 batch_normalization_9[0][0]
__________________________________________________________________________________________________
conv2d_89 (Conv2D) (None, 4, 4, 96) 64608 conv2d_88[0][0]
__________________________________________________________________________________________________
conv2d_85 (Conv2D) (None, 4, 4, 96) 49248 batch_normalization_9[0][0]
__________________________________________________________________________________________________
conv2d_90 (Conv2D) (None, 4, 4, 112) 75376 conv2d_89[0][0]
__________________________________________________________________________________________________
average_pooling2d_8 (AveragePoo (None, 4, 4, 512) 0 batch_normalization_9[0][0]
__________________________________________________________________________________________________
conv2d_86 (Conv2D) (None, 4, 4, 112) 75376 conv2d_85[0][0]
__________________________________________________________________________________________________
conv2d_91 (Conv2D) (None, 4, 4, 112) 87920 conv2d_90[0][0]
__________________________________________________________________________________________________
conv2d_83 (Conv2D) (None, 4, 4, 64) 32832 average_pooling2d_8[0][0]
__________________________________________________________________________________________________
conv2d_84 (Conv2D) (None, 4, 4, 192) 98496 batch_normalization_9[0][0]
__________________________________________________________________________________________________
conv2d_87 (Conv2D) (None, 4, 4, 128) 100480 conv2d_86[0][0]
__________________________________________________________________________________________________
conv2d_92 (Conv2D) (None, 4, 4, 128) 100480 conv2d_91[0][0]
__________________________________________________________________________________________________
concatenate_12 (Concatenate) (None, 4, 4, 512) 0 conv2d_83[0][0]
conv2d_84[0][0]
conv2d_87[0][0]
conv2d_92[0][0]
__________________________________________________________________________________________________
batch_normalization_10 (BatchNo (None, 4, 4, 512) 2048 concatenate_12[0][0]
__________________________________________________________________________________________________
conv2d_98 (Conv2D) (None, 4, 4, 96) 49248 batch_normalization_10[0][0]
__________________________________________________________________________________________________
conv2d_99 (Conv2D) (None, 4, 4, 96) 64608 conv2d_98[0][0]
__________________________________________________________________________________________________
conv2d_95 (Conv2D) (None, 4, 4, 96) 49248 batch_normalization_10[0][0]
__________________________________________________________________________________________________
conv2d_100 (Conv2D) (None, 4, 4, 112) 75376 conv2d_99[0][0]
__________________________________________________________________________________________________
average_pooling2d_9 (AveragePoo (None, 4, 4, 512) 0 batch_normalization_10[0][0]
__________________________________________________________________________________________________
conv2d_96 (Conv2D) (None, 4, 4, 112) 75376 conv2d_95[0][0]
__________________________________________________________________________________________________
conv2d_101 (Conv2D) (None, 4, 4, 112) 87920 conv2d_100[0][0]
__________________________________________________________________________________________________
conv2d_93 (Conv2D) (None, 4, 4, 64) 32832 average_pooling2d_9[0][0]
__________________________________________________________________________________________________
conv2d_94 (Conv2D) (None, 4, 4, 192) 98496 batch_normalization_10[0][0]
__________________________________________________________________________________________________
conv2d_97 (Conv2D) (None, 4, 4, 128) 100480 conv2d_96[0][0]
__________________________________________________________________________________________________
conv2d_102 (Conv2D) (None, 4, 4, 128) 100480 conv2d_101[0][0]
__________________________________________________________________________________________________
concatenate_13 (Concatenate) (None, 4, 4, 512) 0 conv2d_93[0][0]
conv2d_94[0][0]
conv2d_97[0][0]
conv2d_102[0][0]
__________________________________________________________________________________________________
batch_normalization_11 (BatchNo (None, 4, 4, 512) 2048 concatenate_13[0][0]
__________________________________________________________________________________________________
conv2d_108 (Conv2D) (None, 4, 4, 96) 49248 batch_normalization_11[0][0]
__________________________________________________________________________________________________
conv2d_109 (Conv2D) (None, 4, 4, 96) 64608 conv2d_108[0][0]
__________________________________________________________________________________________________
conv2d_105 (Conv2D) (None, 4, 4, 96) 49248 batch_normalization_11[0][0]
__________________________________________________________________________________________________
conv2d_110 (Conv2D) (None, 4, 4, 112) 75376 conv2d_109[0][0]
__________________________________________________________________________________________________
average_pooling2d_10 (AveragePo (None, 4, 4, 512) 0 batch_normalization_11[0][0]
__________________________________________________________________________________________________
conv2d_106 (Conv2D) (None, 4, 4, 112) 75376 conv2d_105[0][0]
__________________________________________________________________________________________________
conv2d_111 (Conv2D) (None, 4, 4, 112) 87920 conv2d_110[0][0]
__________________________________________________________________________________________________
conv2d_103 (Conv2D) (None, 4, 4, 64) 32832 average_pooling2d_10[0][0]
__________________________________________________________________________________________________
conv2d_104 (Conv2D) (None, 4, 4, 192) 98496 batch_normalization_11[0][0]
__________________________________________________________________________________________________
conv2d_107 (Conv2D) (None, 4, 4, 128) 100480 conv2d_106[0][0]
__________________________________________________________________________________________________
conv2d_112 (Conv2D) (None, 4, 4, 128) 100480 conv2d_111[0][0]
__________________________________________________________________________________________________
concatenate_14 (Concatenate) (None, 4, 4, 512) 0 conv2d_103[0][0]
conv2d_104[0][0]
conv2d_107[0][0]
conv2d_112[0][0]
__________________________________________________________________________________________________
batch_normalization_12 (BatchNo (None, 4, 4, 512) 2048 concatenate_14[0][0]
__________________________________________________________________________________________________
conv2d_115 (Conv2D) (None, 4, 4, 128) 65664 batch_normalization_12[0][0]
__________________________________________________________________________________________________
conv2d_116 (Conv2D) (None, 4, 4, 128) 114816 conv2d_115[0][0]
__________________________________________________________________________________________________
conv2d_113 (Conv2D) (None, 4, 4, 96) 49248 batch_normalization_12[0][0]
__________________________________________________________________________________________________
conv2d_117 (Conv2D) (None, 4, 4, 160) 143520 conv2d_116[0][0]
__________________________________________________________________________________________________
max_pooling2d_3 (MaxPooling2D) (None, 1, 1, 512) 0 batch_normalization_12[0][0]
__________________________________________________________________________________________________
conv2d_114 (Conv2D) (None, 1, 1, 96) 83040 conv2d_113[0][0]
__________________________________________________________________________________________________
conv2d_118 (Conv2D) (None, 1, 1, 160) 230560 conv2d_117[0][0]
__________________________________________________________________________________________________
concatenate_15 (Concatenate) (None, 1, 1, 768) 0 max_pooling2d_3[0][0]
conv2d_114[0][0]
conv2d_118[0][0]
__________________________________________________________________________________________________
batch_normalization_13 (BatchNo (None, 1, 1, 768) 3072 concatenate_15[0][0]
__________________________________________________________________________________________________
conv2d_124 (Conv2D) (None, 1, 1, 192) 147648 batch_normalization_13[0][0]
__________________________________________________________________________________________________
conv2d_125 (Conv2D) (None, 1, 1, 224) 129248 conv2d_124[0][0]
__________________________________________________________________________________________________
average_pooling2d_11 (AveragePo (None, 1, 1, 768) 0 batch_normalization_13[0][0]
__________________________________________________________________________________________________
conv2d_121 (Conv2D) (None, 1, 1, 192) 147648 batch_normalization_13[0][0]
__________________________________________________________________________________________________
conv2d_126 (Conv2D) (None, 1, 1, 256) 172288 conv2d_125[0][0]
__________________________________________________________________________________________________
conv2d_119 (Conv2D) (None, 1, 1, 128) 98432 average_pooling2d_11[0][0]
__________________________________________________________________________________________________
conv2d_120 (Conv2D) (None, 1, 1, 128) 98432 batch_normalization_13[0][0]
__________________________________________________________________________________________________
conv2d_122 (Conv2D) (None, 1, 1, 128) 73856 conv2d_121[0][0]
__________________________________________________________________________________________________
conv2d_123 (Conv2D) (None, 1, 1, 128) 73856 conv2d_121[0][0]
__________________________________________________________________________________________________
conv2d_127 (Conv2D) (None, 1, 1, 128) 98432 conv2d_126[0][0]
__________________________________________________________________________________________________
conv2d_128 (Conv2D) (None, 1, 1, 128) 98432 conv2d_126[0][0]
__________________________________________________________________________________________________
concatenate_16 (Concatenate) (None, 1, 1, 768) 0 conv2d_119[0][0]
conv2d_120[0][0]
conv2d_122[0][0]
conv2d_123[0][0]
conv2d_127[0][0]
conv2d_128[0][0]
__________________________________________________________________________________________________
batch_normalization_14 (BatchNo (None, 1, 1, 768) 3072 concatenate_16[0][0]
__________________________________________________________________________________________________
conv2d_134 (Conv2D) (None, 1, 1, 192) 147648 batch_normalization_14[0][0]
__________________________________________________________________________________________________
conv2d_135 (Conv2D) (None, 1, 1, 224) 129248 conv2d_134[0][0]
__________________________________________________________________________________________________
average_pooling2d_12 (AveragePo (None, 1, 1, 768) 0 batch_normalization_14[0][0]
__________________________________________________________________________________________________
conv2d_131 (Conv2D) (None, 1, 1, 192) 147648 batch_normalization_14[0][0]
__________________________________________________________________________________________________
conv2d_136 (Conv2D) (None, 1, 1, 256) 172288 conv2d_135[0][0]
__________________________________________________________________________________________________
conv2d_129 (Conv2D) (None, 1, 1, 128) 98432 average_pooling2d_12[0][0]
__________________________________________________________________________________________________
conv2d_130 (Conv2D) (None, 1, 1, 128) 98432 batch_normalization_14[0][0]
__________________________________________________________________________________________________
conv2d_132 (Conv2D) (None, 1, 1, 128) 73856 conv2d_131[0][0]
__________________________________________________________________________________________________
conv2d_133 (Conv2D) (None, 1, 1, 128) 73856 conv2d_131[0][0]
__________________________________________________________________________________________________
conv2d_137 (Conv2D) (None, 1, 1, 128) 98432 conv2d_136[0][0]
__________________________________________________________________________________________________
conv2d_138 (Conv2D) (None, 1, 1, 128) 98432 conv2d_136[0][0]
__________________________________________________________________________________________________
concatenate_17 (Concatenate) (None, 1, 1, 768) 0 conv2d_129[0][0]
conv2d_130[0][0]
conv2d_132[0][0]
conv2d_133[0][0]
conv2d_137[0][0]
conv2d_138[0][0]
__________________________________________________________________________________________________
batch_normalization_15 (BatchNo (None, 1, 1, 768) 3072 concatenate_17[0][0]
__________________________________________________________________________________________________
conv2d_144 (Conv2D) (None, 1, 1, 192) 147648 batch_normalization_15[0][0]
__________________________________________________________________________________________________
conv2d_145 (Conv2D) (None, 1, 1, 224) 129248 conv2d_144[0][0]
__________________________________________________________________________________________________
average_pooling2d_13 (AveragePo (None, 1, 1, 768) 0 batch_normalization_15[0][0]
__________________________________________________________________________________________________
conv2d_141 (Conv2D) (None, 1, 1, 192) 147648 batch_normalization_15[0][0]
__________________________________________________________________________________________________
conv2d_146 (Conv2D) (None, 1, 1, 256) 172288 conv2d_145[0][0]
__________________________________________________________________________________________________
conv2d_139 (Conv2D) (None, 1, 1, 128) 98432 average_pooling2d_13[0][0]
__________________________________________________________________________________________________
conv2d_140 (Conv2D) (None, 1, 1, 128) 98432 batch_normalization_15[0][0]
__________________________________________________________________________________________________
conv2d_142 (Conv2D) (None, 1, 1, 128) 73856 conv2d_141[0][0]
__________________________________________________________________________________________________
conv2d_143 (Conv2D) (None, 1, 1, 128) 73856 conv2d_141[0][0]
__________________________________________________________________________________________________
conv2d_147 (Conv2D) (None, 1, 1, 128) 98432 conv2d_146[0][0]
__________________________________________________________________________________________________
conv2d_148 (Conv2D) (None, 1, 1, 128) 98432 conv2d_146[0][0]
__________________________________________________________________________________________________
concatenate_18 (Concatenate) (None, 1, 1, 768) 0 conv2d_139[0][0]
conv2d_140[0][0]
conv2d_142[0][0]
conv2d_143[0][0]
conv2d_147[0][0]
conv2d_148[0][0]
__________________________________________________________________________________________________
batch_normalization_16 (BatchNo (None, 1, 1, 768) 3072 concatenate_18[0][0]
__________________________________________________________________________________________________
average_pooling2d_14 (AveragePo (None, 1, 1, 768) 0 batch_normalization_16[0][0]
__________________________________________________________________________________________________
flatten (Flatten) (None, 768) 0 average_pooling2d_14[0][0]
__________________________________________________________________________________________________
dense (Dense) (None, 256) 196864 flatten[0][0]
__________________________________________________________________________________________________
dropout (Dropout) (None, 256) 0 dense[0][0]
__________________________________________________________________________________________________
dense_1 (Dense) (None, 2) 514 dropout[0][0]
==================================================================================================
Total params: 12,173,266
Trainable params: 12,155,986
Non-trainable params: 17,280
__________________________________________________________________________________________________